Preanalytical (Mis)Handling of Plasma Investigated by <sup>1</sup> H NMR Metabolomics

The preanalytical handling of plasma, how it is drawn, processed, and stored, influences its composition. Samples in biobanks often lack this information and, consequently, important information about their quality. Especially metabolite concentrations are affected by preanalytical handling, making conclusions from metabolomics studies particularly sensitive to misinterpretations. The perturbed metabolite profile, however, also offers an attractive choice for assessing the preanalytical history from the measured data. Here we show that it is possible using Orthogonal Projections to Latent Structures Discriminative Analysis to divide plasma NMR data into a multivariate "original sample space" suitable for further less biased metabolomics analysis and an orthogonal "preanalytical handling space" describing the changes occurring from preanalytical mishandling. Apart from confirming established preanalytical effects on metabolite levels, e.g., the consequent changes in glucose, lactate, ornithine, and pyruvate, the sample preparation protocol involved methanol precipitation which allowed the observation of reversible changes in short-chain fatty acid concentrations as a function of temperature.

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Publication Details

Journal
ACS Omega
Published
2024-11-27
DOI
https://doi.org/10.1021/acsomega.4c08215
Citations
2
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
0.47
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article

Preanalytical (Mis)Handling of Plasma Investigated by 1 H NMR Metabolomics

Göran Karlsson, Linda Paulson, Åsa Torinsson Naluai, Huma Zafar et al.
2 citations
ACS Omega
Metabolomics and Mass Spectrometry Studies
0.47
article

Preanalytical (Mis)Handling of Plasma Investigated by 1 H NMR Metabolomics

Göran Karlsson, Linda Paulson, Åsa Torinsson Naluai, Huma Zafar, Daniel Malmodin, Anders Bay Nord
article en
2 citations

Abstract

The preanalytical handling of plasma, how it is drawn, processed, and stored, influences its composition. Samples in biobanks often lack this information and, consequently, important information about their quality. Especially metabolite concentrations are affected by preanalytical handling, making conclusions from metabolomics studies particularly sensitive to misinterpretations. The perturbed metabolite profile, however, also offers an attractive choice for assessing the preanalytical history from the measured data. Here we show that it is possible using Orthogonal Projections to Latent Structures Discriminative Analysis to divide plasma NMR data into a multivariate "original sample space" suitable for further less biased metabolomics analysis and an orthogonal "preanalytical handling space" describing the changes occurring from preanalytical mishandling. Apart from confirming established preanalytical effects on metabolite levels, e.g., the consequent changes in glucose, lactate, ornithine, and pyruvate, the sample preparation protocol involved methanol precipitation which allowed the observation of reversible changes in short-chain fatty acid concentrations as a function of temperature.

ACS OmegaVol. 9(49)
Swedish National Bank (SE), University of Gothenburg (SE)
Openalex Percentile: Top 34%
Metabolomics and Mass Spectrometry Studies
0.47
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